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Dynamic power allocation for a multiuser transmitter with hybrid energy sources

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Version 2 2024-06-21, 10:02
Version 1 2020-02-19, 15:55
journal contribution
posted on 2024-06-21, 10:02 authored by D Liu, J Lin, J Wang, F Jiang
© 2017, The Author(s). In this paper, we investigate the problem of dynamic power allocation for a multiuser transmitter supplied by hybrid energy sources in details. Specifically, we focus on the hybrid energy sources which include both the traditional power grid and various renewable sources whereby there are a few issues in considerations: (1) The energy harvested jointly from various renewable sources is time-varying and possibly unpredictable and is stored in a limited capacity buffer with battery leakage. (2) At the meantime, the data arrives randomly to the transmitter and queues according to the individual receivers to wait to be transmitted. (3) In addition, the wireless channels fluctuate randomly due to fading. Taking into account the time variant and dynamic features of this system, we develop a dynamic power allocation algorithm for the transmitter with the aim of minimizing the average amount of energy consumption from the power grid over an infinite horizon, subject to all data in queues cannot exceed a given deadline of receivers. The research question is formulated as a stochastic optimization problem, then we utilize Lyapunov optimization to exploit an online algorithm with low complexity, and it does not require prior statistical knowledge of the stochastic processes. Performance analysis of the proposed algorithm is carried out in theory, which shows that the proposed algorithm performs arbitrarily close to the optimal objective value; meanwhile, the algorithm ensures that the maximum delay of all data queues cannot exceed a given value. Finally, performance comparison shows that our proposed algorithm provides not only better performance but also less time delay than other two algorithms.

History

Journal

EURASIP Journal on Wireless Communications and Networking

Volume

2017

Article number

203

Pagination

1-12

Location

Berlin, Germany

Open access

  • Yes

ISSN

1687-1472

eISSN

1687-1499

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal

Issue

1

Publisher

SpringerOpen